Designing a driveline is complex and time consuming. The engineer needs to know that the driveline is fit for purpose before it is made and to determine this various analytical methods are used to determine judge the performance or likelihood of failure, followed by optimisation to change the product definition so as to maximise the product performance. Analysis, either by mathematical simulation or other methods such as benchmarking (comparison with similar products), is typically carried out in a computer program and the domain of computer-aided engineering (CAE) has grown based on this intention.
The process of setting up the analysis for a given failure mode or aspect of performance requires creating a model of the system, sub-assemblies and components. Thus the process becomes one of (i) Modelling, (ii) Analysis, (iii) and Optimisation. A failure mode includes what constitutes a failure in terms of performance.
Different aspects of product performance need to be considered in the design process, including (but is not limited to): vehicle/product performance, energy/fuel efficiency/economy, exhaust gas emissions, packaging within the space constraints, cost, weight, structural deflections and stress, durability and fatigue, manufacturability, thermal performance, generation of audible noise, mechanical failure due to dynamic input loads, generation of dynamic loads adverse to the user and/or environment, speed and ratio changing, and satisfactory interaction with a control system.
To assess these different failure modes and aspects of performance, different mathematical analysis methods are used and these require different models of the system, consisting of different data. As a result, it is typical for CAE models for each failure mode to be built specifically for that failure mode. This is illustrated FIG. 1. Indeed, often CAE packages are developed specifically for the purpose of assessing a given failure mode.
To predict the performance of each component or sub-system often requires different computational algorithms. Also, the components are sub-systems are often designed and manufactured by different departments or companies. Thus, often the simulation of that component or sub-system focuses on the component or sub-system alone and ignores or simplifies the interactions that occur with other components or sub-systems. The result can be inaccurate predictions of product performance.
The design of the system evolves as a result of a process, as opposed to undergoing an instantaneous moment of creation. Some of the parameters defining the design are defined at the start of the process; others are not defined until the end.
As a result, the different analyses of product performance are carried out at different stages in the design process. Not all the methods are possible at the start. Typically, only relatively simple analyses are possible when the product definition is light, and it is only towards the end of the design process that more complex analyses are possible.
Moreover, for the same failure mode, a simple analysis may be carried out early in the design process and then the a more complex analysis may be carried out later on for the same failure mode, because the product definition is more mature and contains greater fidelity.
Therefore it can be seen that different models have different purposes and are used at different stages in the design process. No single model definition can be used for the complete design and optimisation of a driveline and the different models, each with their different features and different strengths and weaknesses, are used at different stages of the design process and by different engineering professionals.
This means that a team of designers will use a number of separate applications for analysing the performance of the driveline. To analyse the model at different levels of complexity, they will need to use separate applications for the same performance measure. In addition, a model suitable for mathematical analysis for one performance measure will not be suitable for another. Each member of the design team will need to exercise his or her own knowledge and experience to know (i) what application to select, (ii) what model and level of accuracy to use and (iii) what analysis is required to get the desired result.
In addition, there is a risk that the user will use a detailed analysis when the information describing the rotating machine assembly (input data) merits only a simple analysis; this may lead to errors in the analysis, yet the user may not know.
Furthermore, because the models are created manually, and in different applications, a change in the information describing the rotating machine assembly (product definition) does not, and often cannot, get cascaded to other analyses run in different applications.
This is particularly acute when considering a specific division in engineering activity that takes place during the creation of a product, that between design and analysis. Design, at least for the mechanical engineer, is often considered to concern the definition of the geometry of the product, whereas analysis studies the product in terms of how it functions for the aspects of performance or failure modes. In fact, the geometry that is considered in design is just another aspect of performance—it deals with the question of how the product fits the packaging space available. Yet this aspect of performance is typically dealt with by a completely different computer programme, CAD (Computer Aided Design), which has little or no calculation capability to predict other aspects of product performance, and poor or non-existent links to the analysis packages that do. CAD packages are typically operated by design engineers and analysis packages by analytical engineers. The result is a disconnect in the design process, poor productivity, sub-optimal products and wasted economic activity.
There is a further problem with complex analyses. The purpose of any analysis is to guide the design of the product, and so the value of the analysis comes when the result of the analysis is correctly interpreted/understood by the engineering team and the corresponding design decision is made. For a result to be understood, it needs to “make sense” to the engineers and correspond to the way that the engineers understand the system to perform. However, once an analysis becomes highly complex, it is possible that the result will be too complex to be understood or that it does not match the engineers' fundamental understanding of its performance. Thus, even though the analysis result may be the most accurate analysis possible, it will be discarded in the engineering decisions regarding the system.
It is an irony that the engineers' fundamental understanding of the system performance is very closely related to the simple analyses which may have been carried out at the start of the design process. Thus, the tension exists—there is a desire to increase complexity since this is assumed to increase accuracy and product performance, yet take this too far and complex analysis ceases to be of use.
The purpose of these analyses is to avoid failure modes. As the design matures through the design process, the increase in data definition represents an increase in monetary investment into the design, so any identification of failure mode needs to be achieved at the earliest possible opportunity, thereby minimising the financial cost of iterative re-work.
This points to a final tension in the process. The process needs to provide speed of modelling and analysis to give the productivity, yet include all the system influences to provide the accuracy. Analysing a larger system with all of the system influences tends to lead towards a more complex analysis, yet as has been discussed this leads to problems with speed of modelling and analysis and in data interpretation.
The solution to this for many has been the development of application specific software packages, where the modelling and analysis functions are pre-defined for a given type of product or application. This allows the desired accuracy of modelling and analysis to be achieved without requiring every product being described from first principles, thereby maintaining productivity.
The current process that has been described for product design is one of creating models of the driveline so as to analyse various failure modes. Due to the natural hierarchy of the order in which design parameters are defined, and the different requirements for each analysis, the different analyses are carried out at different stages in the design process. Hence the design process consists of different representations of the same driveline being created at different stages for different analysis purposes.
One of the key performance criteria of a driveline can be referred to as Vehicle Performance, and this can be assessed very early in the design process, using a simple model that can be referred to as a “Block Diagram”.
This consists of the major sub-assemblies: engine, gearbox, motor, battery, fuel tank and vehicle. Lines connect the sub-assemblies and denote the functional connection by which power is transmitted from one sub-assembly to another. This power can be in the form of either rotational mechanical power (between the engine, motor, gearbox and vehicle), electrical power (between the battery and motor) or chemical power (between the fuel tank and the engine). An example is given in FIG. 2.
The physical embodiment of the system means that rotational mechanical power is transmitted by a rotating shaft, electrical power by wires and chemical power by a fuel line. However, this detail is not required by the engineer, who simply wishes to view and understand the flow of power and energy within the driveline. Note that no geometric detail exists to describe the physical proportions of the systems or their proximity to one another.
Further properties can be assigned to the sub-assemblies. For example, a graph of torque and power against speed for the engine and motor, a set of gear ratios for the gearbox and mass, drag coefficient, rolling resistance, frontal area and tyre rolling radius for the vehicle. From this data, a simulation or analysis can be carried out to derive the vehicle performance (speed versus time, maximum speed etc.).
Still more functional properties can be assigned to the sub-assemblies. Efficiencies of the motor, gearbox and engine can be defined either as constant values or as graphs of efficiency against speed and torque (more complex relationships can also be defined, dependent on other parameters) and the vehicle can be “driven”, in a virtual sense, around a certain drive cycle (speed versus time profile).
It is possible to derive values for the fuel economy and emissions of the vehicle for given drive cycles, driving styles etc. This is particularly common given the increasing requirement for low carbon vehicles, and this is another failure mode that needs to be assessed. This work is carried out in many different companies across the world and it is embodied in many different CAE packages. These CAE packages are typically Multi-domain dynamic simulation which can be divided into the two sub-categories of Generalist CAE packages (for example Simulink, Dymola, Modellica) and Application-specific vehicle simulation packages such as AVL Cruise and GT-Suite. In GB2470385A, a simulation model relies on components, also referred to as “virtual components”, each of which is a model representing a component of the rotary machine within the system and comprising an algorithm. Each model reads in a stream of input data and transforms it into a stream of output data using its model algorithm. The properties of the models are exemplified as being lower and upper bounds of values, linear or non-linear relationships, initial value of differential equations and degree of complexity of analysis by the algorithm of the model.
As has been stated, a key aspect of product performance is packaging, i.e. the product must physically fit within the available space. For this, the system, sub-assemblies and components need their 3D geometry to be defined, and this is typically carried out in 3D CAD packages such as Wildfire, Solid Works, Catia, Unigraphics etc.
To such 3D CAD definitions can be added the density of the materials that are used, which allows the weight of the system, sub-assemblies and components to be calculated. This allows another aspect of product performance, weight, to be calculated.
It is a key aspect of the current software products that include the functions for assessing engineering performance (vehicle performance, efficiency, fuel economy) are in separate products from those that consider the 3D geometry, packaging and weight. Looking at the specific example of the gearbox, software products that assess vehicle performance, efficiency and fuel economy require the gearbox to be represented only in terms of its ratios, and perhaps the inertia and maybe torsional stiffness of the gearbox and its shafts. In effect, the gearbox occupies no 3D space and only has properties that relate to rotation about the axis or axes that transmit power.
Other aspects of engineering performance are considered in still further software packages. These aspects of engineering performance include structural deflections and stress, durability and fatigue, manufacturability, thermal performance, generation of audible noise, mechanical failure due to dynamic input loads, generation of dynamic loads adverse to the user and/or environment, speed and ratio changing, and satisfactory interaction with a control system. These are discussed in subsequent paragraphs.
Mechanical power transmission involves inducing stresses on components, which may cause catastrophic failure due to overload, fatigue failure or wear. It is typical to calculate the operating loads within a system, calculate the deflections and stresses of the components and hence the durability of the components and thus the whole system. Such simulations are typically embodied in generalist Finite Element packages such as Nastran, Ansys or Abaqus or application specific packages such as RomaxDesigner, KissSoft (for gearboxes) and AVL Excite (for engines).
Other application specific packages are developed for other sub-systems such as motor and generators, which are the subject of packages such as Opera, SPEED and JMAG.
Within the gearbox, gears are key components, which are required to be durable, quiet and efficient, and at the same time fit within the available space and also be manufacturable. It is typical to calculate the stress (for durability), efficiency and generated vibration for the gear, but sometimes this is done without regard for the manufacturability of the gear. A key aspect is how the shape of the cutting tool for the gear, and in particular the protuberance of the hob, shaper or milling cutter affects the shape of the gear and thus the results for the durability, noise and efficiency. Failure to account for these aspects of manufacturability can result in inaccurate results.
With regard to dynamic analysis, the complexity of the mathematical representation varies greatly depending on the failure mode being studied. Examples are given below:
A “Drive cycle simulation” is a dynamic analysis where, for example, a road going vehicle is simulated being driven along a certain route consisting of varying speeds. This has been described previously, with regard to “block diagram” modelling. For this simulation, the failure mode/performance criteria are fuel economy and CO2 emissions.
An “Acoustic simulation” is where the structure of a driveline is excited by some periodically repeating forcing such as engine firing (from an internal combustion engine), torque ripple (from a motor) or transmission error (from a gear mesh). The driveline structure (including rotating components such as shafts and gears and structural components such as housings, casings etc.) vibrates in response to this excitation. This forced response is calculated and the results of interest are the vibration at the driveline mount positions (this gets transmitted to the structure of the vehicle, for example) or the vibration at the surfaces of an external housing (this can be converted to a radiated acoustic signal). Such simulations are typically embodied in generalist FE packages such as Nastran, Ansys and Abaqus or generalist multi-body packages such as ADAMS or Simpack. For this simulation, the failure mode/performance criteria is noise, vibration and harshness.
Various “Driveline transient simulations” are carried out which look at the phenomenon where a power transmitting driveline consisting of rotating components is subject to rapid changes in driving torque or speed.
In one instance, the response of the driveline may include the reversing of the sign of the torque, leading to components with backlash such as gears and splines travelling across the backlash region and experiencing impact loads. Such simulations are typically embodied in generalist multi-body packages such as ADAMS or Simpack. For this simulation, the failure mode/performance criteria is a high shock load within the system or an impact that can be heard or felt by the operator.
In another instance, the change in torque may come from the vehicle driving over a bump or the electric motor experiencing a grid fault or electrical short. The response of the driveline may include the high loads on key components (leading to durability problems) or the acceleration/deceleration of the vehicle (unpleasant for the occupants). Such simulations are typically embodied in generalist multi-body packages such as ADAMS or Simpack. For this simulation, the failure mode/performance criteria is a high shock load within the system or a change in acceleration felt by the operator.
Three examples of different dynamic simulations for drivelines have been described. Others can be described, including gear rattle, tip-in/tip-out, imbalance, gear shift quality and engagement of two-speed generators in wind turbines.
Some of these dynamic phenomena are related to the sub-system and some are related to the full driveline system. As such, they are of interest to, and are influenced by, component suppliers (e.g. bearing and synchroniser suppliers), sub-system suppliers (e.g. gearbox, engine, motor, driveshaft suppliers) and vehicle manufacturers.
In many cases, the behaviour of the sub-system is influenced by the detailed characteristics of the components, and the behaviour of the driveline is influenced by the detailed characteristics of the sub-system. Thus detailed design information needs to be passed from component supplier to sub-system supplier and sub-system supplier to vehicle manufacturer. However, this process is impeded since the component and sub-system suppliers are often unwilling to divulge the detailed design information of their products due to reasons of confidentiality.
It is possible for dynamic models of sub-systems to be packaged up into a sub-model. These are sometimes referred to as “S-functions” (in the case of multi-domain simulation packages such as Simulink) or super-elements (in the case of finite element and multi-body dynamics packages).
In any case, since the details of such models are hidden, it is essential that they have the correct level of detail for the simulation of a given dynamic phenomenon or failure mode. The recipient of the model depends on the model formulation being correct for the accuracy of the simulation results that will be obtained, yet often dynamic models are set up in a sub-optimal manner.
As the design of the product and the sub-systems proceeds, further analyses are carried out. It is common for the electric motor or generator to be designed by motor/generator specialists or companies and likewise for gearboxes. The temptation is to assume that the two sub-systems assemble together without problems and the other sub-system is a benign receiver or deliverer of rotating power. Thus the sub-systems are designed and analysed in separate mathematical models, with the assumption that a smooth, invariant passage of torque is delivered though a perfectly aligned shaft.
In fact, when power is transmitted through a gearbox, separating forces at the gears cause the shafts to bend, the bearings to deflect and the housing to deflect. When power is generated in the motor, the rotor is subject to unbalanced magnetic pull and any shaft deflections or run out will lead to the rotor being pulled off centre. These forces (plus moments) and deflections (plus misalignments) are important in calculating the loads on the bearings and hence bearing life, and gear stress, life, noise and efficiency. Also, the air gap in the motor, which affects the motor efficiency, is also affected.
It is possible to calculate the effect of loads and deflections within a gearbox and their effect on gearbox performance within a gearbox simulation. Likewise, it is possible to calculate the unbalanced magnetic pull in a motor using a motor simulation. However, interactions between the two sub-systems are not considered.
This is becoming increasingly important as the design of compact electro-mechanical drivelines requires that motors and gearboxes are becoming more and more integrated, so such interactions are becoming more important.
Understanding the dynamic behaviour of any product often involves creating a mathematical model from which the natural frequencies and mode shapes can be derived. This is the most effective starting point when the product behaves in a linear or predominantly linear manner.
It is possible to calculate the natural frequencies and mode shapes of a gearbox using generalist tools such as Finite Element Analysis (e.g. Ansys, Nastran) or Multi-Body Dynamics (e.g. ADAMS) or specialist tools such as RomaxDesigner or MASTA. Similarly, it is possible to calculate the natural frequencies and mode shapes of the structural (mechanical) parts of the motor using the same tools. However, the natural frequencies and mode shapes of the complete assembly require that the interactions between the two sub-systems are considered.
Again, this is becoming increasingly important as the design of compact electro-mechanical drivelines requires that motors and gearboxes are becoming more and more integrated, so such interactions are becoming more important.
Further, the definition of the natural frequencies and mode shapes of a system requires that all the relevant masses and stiffnesses of the system are correctly included. Often, the stiffnesses within a mechanical system relate solely to the contact and tensile stiffnesses of the mechanical components. However, in the case of a motor, the unbalanced magnetic pull on the rotor arising from the electromagnetic forces also constitutes a stiffness, in fact a negative stiffness. This affects the natural frequencies and mode shapes of the system but is not currently considered.
When power is generated by a motor and transmitted by a gearbox, dynamic excitations are generated in the form of torque ripple and varying electromagnetic forces in the motor and gear transmission error and run out in the gearbox. These excitations propagate through the driveline, resulting in noise radiation.
It is possible to calculate the dynamic response and acoustic radiation of a gearbox using generalist tools such as Finite Element Analysis (e.g. Ansys, Nastran) or Multi-Body Dynamics (e.g. ADAMS) or specialist tools such as RomaxDesigner or MASTA, combined with acoustic simulation tools such as Coustyx. Similarly, it is possible to calculate the dynamic response and acoustic radiation of the structural (mechanical) parts of the motor using the same tools.
However, the dynamic response and acoustic radiation of the complete assembly require that the interactions between the two sub-systems are considered. The torque ripple, transmission error and electromagnetic forces excite the whole gearbox/motor structure. This does not occur if the sub-systems are simulated in separate mathematical models.
Also, the air gap in the motor, which affects the motor efficiency, is also affected by the dynamic response of the system to unbalanced magnetic pull, out of balance mass, deflections of the rotor shafts and component manufacturing tolerances, but this is not calculated and instead values for the air gaps are either estimated or carried over from previous designs.
The previous paragraphs talk about the requirements for an accurate and complex mathematical model of the gearbox and/or motor system for the purposes of assessing the dynamic response and acoustic radiation. The source of acoustic radiation is the gearbox/motor housing, so to calculate the acoustic radiation the housing needs to modelled in substantial detail so that it can be included in the simulation of the system.
However, this presents a problem when applying the methods to the practical design of products since, at the concept design stage, the engineer is interested in major changes to the layout such as changing bearing and gear positions, shaft centre distances, even number of shafts. Therefore, no housing design exists. Technical investigations have shown that the calculated dynamic response of a motor, gearbox or electro-mechanical driveline system is very different depending on whether a concept model is used (with the outer races of the roller bearings held rigid) or a detailed model is used (with the outer races of the roller bearings attached to the mass/stiffness representation of the housing).
Therefore, the design engineer is unable to determine by simulation which concept design is likely to be best or worst performing when it comes to dynamic response to torque ripple and transmission error. Currently, the engineer needs to select a concept without such knowledge and invest time and money in designing a housing before any such simulation can be carried out.